Optimal WACC in tariff regulation under uncertainty

被引:0
|
作者
Ward Romeijnders
Machiel Mulder
机构
[1] University of Groningen,Department of Operations, Faculty of Economics and Business
[2] University of Groningen,Department of Economics, Econometrics & Finance, Faculty of Economics and Business
来源
关键词
Tariff regulation; Weighted average cost of capital; Electricity grid; D25; D42; Q48; L51; L94;
D O I
暂无
中图分类号
学科分类号
摘要
In the regulation of network tariffs, the compensation for the opportunity costs of capital through the Weighted Average Costs of Capital (WACC) plays a crucial role. Determining the appropriate level for the WACC is, though, problematic because of the uncertainty about the future conditions in capital markets. When the WACC is set above the future opportunity costs of capital, consumers will pay too much, while when the WACC is below that level, network operators may be unable to finance investments affecting quality of network services. In this paper, we explicitly take this uncertainty into account when we determine the optimal WACC for the tariff regulation of an electricity network. By trading off consumer surplus and expected disruption costs in the electricity grid, we conclude that from a social-welfare perspective in most cases the optimal WACC in tariff regulation is above the historical mean costs of capital. Only in case of high uncertainty about the true costs of capital while network operators are able to quickly increase investment levels, the optimal WACC is below the historical mean because then it is less likely that the WACC is constantly insufficient to cover actual costs of capital. However, when network operators cannot quickly increase investment levels the optimal WACC is always above the historical mean cost of capital.
引用
下载
收藏
页码:89 / 107
页数:18
相关论文
共 50 条
  • [21] Optimal tariff design under consumer self-selection
    Rasanen, M
    Ruusunen, J
    Hamalainen, RP
    ENERGY ECONOMICS, 1997, 19 (02) : 151 - 167
  • [22] Optimal Bidding Strategy for V2G Regulation Services under Uncertainty
    Bae, Sangjae
    Zhang, Hongcai
    Wang, Dai
    Sheppard, Colin
    Saxena, Samveg
    2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2017,
  • [23] Regulation under uncertainty: The coevolution of industry and regulation
    Sabel, Charles
    Herrigel, Gary
    Kristensen, Peer Hull
    REGULATION & GOVERNANCE, 2018, 12 (03) : 371 - 394
  • [24] Mobile capital, optimal tariff, and tariff war
    Takatsuka, Hajime
    Zeng, Dao-Zhi
    REVIEW OF INTERNATIONAL ECONOMICS, 2022, 30 (01) : 166 - 204
  • [25] Optimal Intertemporal Consumption under Uncertainty
    Chamberlain, Gary
    Wilson, Charles A.
    REVIEW OF ECONOMIC DYNAMICS, 2000, 3 (03) : 365 - 395
  • [26] OPTIMAL PROCESS DESIGN UNDER UNCERTAINTY
    HALEMANE, KP
    GROSSMANN, IE
    AICHE JOURNAL, 1983, 29 (03) : 425 - 433
  • [27] OPTIMAL ARBITRAGE UNDER MODEL UNCERTAINTY
    Fernholz, Daniel
    Karatzas, Ioannis
    ANNALS OF APPLIED PROBABILITY, 2011, 21 (06): : 2191 - 2225
  • [28] OPTIMAL PROCESS DESIGN UNDER UNCERTAINTY
    OSTROVSKY, GM
    VOLIN, YM
    DOKLADY AKADEMII NAUK, 1992, 325 (01) : 103 - 106
  • [29] Optimal corporate strategy under uncertainty
    Chen, Andrew H.
    Fabozzi, Frank J.
    Huang, Dashan
    APPLIED ECONOMICS, 2013, 45 (20) : 2877 - 2882
  • [30] Optimal Dividends Under Model Uncertainty*
    Chakraborty, Prakash
    Cohen, Asaf
    Young, Virginia R.
    SIAM JOURNAL ON FINANCIAL MATHEMATICS, 2023, 14 (02): : 497 - 524